Clinical practice guideline for the management of paediatric Charcot-Marie-Tooth disease
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Charcot-Marie-Tooth disease (CMT) is the most common inherited neuropathy and often presents during childhood. Guidelines for the optimal management of common problems experienced by individuals with CMT do not exist, for either children or adults. We formed the Paediatric CMT Best Practice Guidelines Consortium to develop evidence and consensus-based recommendations for the clinical management of children and adolescents with CMT, with the primary objective of promoting optimal, standardised care globally. METHODS: Development of this clinical practice guideline involved a series of systematic reviews covering 10 clinical questions, modified Delphi methodology involving an international panel of clinicians to generate consensus where evidence did not exist, and application of the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach to evaluate the body of literature and formulate recommendations. RESULTS: The final guideline includes three evidence-based and 31 consensus-based recommendations. They encompass the management of muscle weakness, balance and mobility impairment, sensory symptoms, muscle cramps, impaired upper limb function, respiratory impairment, maintenance of joint range of motion and non-surgical management of joint deformity. Consensus was not achieved in some management areas, reflecting differences in practice between clinicians and healthcare settings, and highlighting the need for further research. CONCLUSIONS: This clinical practice guideline provides practical and implementable guidance on the management of common clinical problems experienced by children with CMT and advocates for improved access to multidisciplinary care. Successful dissemination and implementation of these recommendations will be critical in ensuring their application across multiple healthcare settings.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.014 | 0.010 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".